A new approach to improve accuracy of grey model GMC (1,n) in time series prediction

© 2015 Sompop Moonchai and Wanwisa Rakpuang. This paper presents a modified grey model GMC(1,n) for use in systems that involve one dependent system behavior and n-1 relative factors. The proposed model was developed from the conventional GMC(1,n) model in order to improve its prediction accuracy by...

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Main Authors: Sompop Moonchai, Wanwisa Rakpuang
Format: Journal
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84953214867&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/44670
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-446702018-04-25T07:53:24Z A new approach to improve accuracy of grey model GMC (1,n) in time series prediction Sompop Moonchai Wanwisa Rakpuang Agricultural and Biological Sciences © 2015 Sompop Moonchai and Wanwisa Rakpuang. This paper presents a modified grey model GMC(1,n) for use in systems that involve one dependent system behavior and n-1 relative factors. The proposed model was developed from the conventional GMC(1,n) model in order to improve its prediction accuracy by modifying the formula for calculating the background value, the system of parameter estimation, and the model prediction equation. The modified GMC(1,n) model was verified by two cases: the study of forecasting CO 2 emission in Thailand and forecasting electricity consumption in Thailand. The results demonstrated that the modified GMC(1,n) model was able to achieve higher fitting and prediction accuracy compared with the conventional GMC(1,n) and D-GMC(1,n) models. 2018-01-24T04:46:25Z 2018-01-24T04:46:25Z 2015-01-01 Journal 16875605 16875591 2-s2.0-84953214867 10.1155/2015/126738 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84953214867&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/44670
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Agricultural and Biological Sciences
spellingShingle Agricultural and Biological Sciences
Sompop Moonchai
Wanwisa Rakpuang
A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
description © 2015 Sompop Moonchai and Wanwisa Rakpuang. This paper presents a modified grey model GMC(1,n) for use in systems that involve one dependent system behavior and n-1 relative factors. The proposed model was developed from the conventional GMC(1,n) model in order to improve its prediction accuracy by modifying the formula for calculating the background value, the system of parameter estimation, and the model prediction equation. The modified GMC(1,n) model was verified by two cases: the study of forecasting CO 2 emission in Thailand and forecasting electricity consumption in Thailand. The results demonstrated that the modified GMC(1,n) model was able to achieve higher fitting and prediction accuracy compared with the conventional GMC(1,n) and D-GMC(1,n) models.
format Journal
author Sompop Moonchai
Wanwisa Rakpuang
author_facet Sompop Moonchai
Wanwisa Rakpuang
author_sort Sompop Moonchai
title A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
title_short A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
title_full A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
title_fullStr A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
title_full_unstemmed A new approach to improve accuracy of grey model GMC (1,n) in time series prediction
title_sort new approach to improve accuracy of grey model gmc (1,n) in time series prediction
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84953214867&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/44670
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